output
20182022
most citedLearning a Probabilistic Model for Diffeomorphic Registration

250 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing cs.CVShow all

6 papers · 1 filter

cs.CV2022

Privacy Preserving Image Registration

Riccardo Taiello, Melek Önen, Francesco Capano +2

Image registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame. Current approaches to image registration…

cs.CV2021

Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation

Vien Ngoc Dang, Francesco Galati, Rosa Cortese +7

Deep learning techniques for 3D brain vessel image segmentation have not been as successful as in the segmentation of other organs and tissues. This can be explained by two factors…

cs.CV2018★ 250 cited

Learning a Probabilistic Model for Diffeomorphic Registration

Julian Krebs, Hervé Delingette, Boris Mailhé +2

We propose to learn a low-dimensional probabilistic deformation model from data which can be used for registration and the analysis of deformations. The latent variable model maps…

cs.CV2018★ 4 cited

3D Consistent & Robust Segmentation of Cardiac Images by Deep Learning with Spatial Propagation

Qiao Zheng, Hervé Delingette, Nicolas Duchateau +1

We propose a method based on deep learning to perform cardiac segmentation on short axis MRI image stacks iteratively from the top slice (around the base) to the bottom slice (arou…

cs.CV2018★ 47 cited

Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training

Wen Wei, Emilie Poirion, Benedetta Bodini +4

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS). A reliable measure of the tissue myelin content is therefore essential for the understanding…

cs.CV2018★ 2 cited

3D Consistent Biventricular Myocardial Segmentation Using Deep Learning for Mesh Generation

Qiao Zheng, Hervé Delingette, Nicolas Duchateau +1

We present a novel automated method to segment the myocardium of both left and right ventricles in MRI volumes. The segmentation is consistent in 3D across the slices such that it…